IITA IFAD High Quality Cassava Value Chain project...
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High Quality Cassava Flour (HQCF) Value Chain project is supported by the International Fund for Agricultural Development (IFAD) and led by the International Institute of Tropical Agriculture (IITA). HQCF Value Chain project aims at enhancing the competitiveness of high quality cassava flour value chain project in Nigeria. In a bid to actualize and enrich this aim, the project has developed profitable and cost effective measures towards planting and harvesting cassava roots. This achievement was based on data collection tools to monitor the extent of the improved methods of production (including the use of high quality production inputs superior germplasm, fertilizer and weed management with herbicides, mechanical planting, etc.) are more cost-effective, profitability and competitiveness of production operations compared with traditional production system in each of the project innovation platforms.
Introduction and purpose of evaluation IFAD-IITA HQCF introduced mechanical planting cassava stems and harvesting fresh cassava roots from 2015/2016 for testing by farmers in HQCF innovation platforms. The purpose of output 4 of the monitoring and evaluation (M&E) of the HQCF project was to compare the costs and benefits of the new innovation (mechanical planting and harvesting) with the traditional manual practices of planting and harvesting cassava. This new innovation was assessed and compared with manual planting and harvesting in terms of cost- effectiveness, profitability and
competiveness of the cassava production operations.
Methodology Key Informants Interview (KII) and partial budgeting techniques were used to examine the cost- effectiveness, profitability and competitiveness of cassava production operations1. The KII was held with farmers that used mechanical planter and harvester to assess their perceptions. The partial budgeting was used to compare the costs and benefits of the new innovation with the manual planting and harvesting. The comparison was based on cassava production operations data obtained from Open Door HQCF Innovation platform and farmers that used manual planting and harvesting techniques.
Partial budgeting Partial budgeting is a planning and decision-making framework used to compare the costs and benefits of
alternatives faced by a farm business. It focuses only on the changes in income and expenses that would result from implementing a specific alternative. Thus, all aspects of farm profits that are unchanged by the decision can be safely ignored. In a nutshell, partial budgeting allows you to get a better handle on how a decision will affect the profitability of the enterprise, and ultimately the profitability of the farm itself.
Partial budgeting was used to determine and compare the profitability in cassava production using mechanized planting compared with manual planting techniques. The process provided actual information on farm-input use and costs, output and prices, and farmers’ gross margins. The gross margin budget examines the returns to the farmers’ resources, which consist mainly of labour used, capital inputs such as fertilizer, chemicals and other production inputs. The procedure involved the estimation of the costs and returns based on 2015/2016 cassava production season.
Profitability and cost effective measures
Suggested Recommendations The results of the partial budgeting have clearly shown that mechanized method of cassava production is very profitable and cost effective. The yield form mechanized process almost double the manual process, while the costs associated with planting and harvesting using mechanized process is less than 50% of cost spent by manual process.
The following suggested recommendations are based on the results of the KII held with farmers and the partial budgeting analysis of cassava production carried out in Open Door HQCF Innovation Platform:-
yy Farmers should intensify efforts to create awareness among cassava farmers with regards
to the adoption of mechanized process in cassava production. Such awareness can be created through field days whereby the results of this partial budgeting can be presented, production of fliers and briefs.
yy The partial budgeting analysis has revealed increased profitability of using mechanized planting and harvesting technologies in cassava production. There should be increased efforts to scale-up the promotion and dissemination of these mechanical planters and harvester among cassava farmers in the project areas. In addition, the HQCF value chain project should build the capacity of cassava farmers with regards to improved
cassava production technologies and crop management practices.
yy During the coming season, partial budgeting should be undertaken together with farmers i.e. participatory partial budgeting) so that the farmers can better appreciate the economic viability of using mechanized production process.
yy The HQCF value chain project should start identifying and create awareness among entrepreneurs that can provide mechanized planting and harvesting services for interested farmers for fees. This is an area that we can encourage the emerging Agripreneurs to go into and link them to credit institutions and equipment leasing companies.
For enquiry, contact Project manager: firstname.lastname@example.org, Data analyst/Curator: email@example.com,
Communication officer: firstname.lastname@example.org
Table 1: Cassava production comparison of mechanized and manual planting in Open Door HQCF Innovation Platform, Ogun State1.
INCrEASE % INCrEASE
Fresh roots ton ha-1 16 22 9.3 38%
Cassava price (Naira/ton) 12,000 12,000
revenue from Output (Naira) 192,000 264,000 72,000 38%
Variable costs ha-1
Land Preparation 27000 25000 -2,000 -8%
Purchased inputs 38,000 47,000 9,000 24%
Planting 9,000 4,000 -5,000 -55%
harvesting 18,847 7,600 -11,247 -60%
Manual weeding 6,000 12,000 6,000 100%
Herbicide application 2,000 8,000 6,000 300%
Miscellaneous & root transportation 9,500 11,000 1,500 16%
Total variable inputs 110,347 114,600 4,253 4%
Margin (N per ha-1) 81,653 149,400 67,747 83% Source: Analysis of field data, 2016